Monitoring and detection of algae in surface water and wastewater is of significant importance, yet there is currently no quick and simple method to achieve this. The present work illustrates a new method to determine the concentration of algae in water and wastewater samples using spectrophotometry, the first derivative of absorbance, and a smoothing technique applied to the first derivative of absorbance (e.g. Savitzky-Golay). The relationship between algal concentration and absorbance for three types of water samples (distilled, surface, and wastewater) was determined in the visible wavelength range, and the effect of using the first derivative of absorbance method on improving algal concentration detection limit was established. Using the first derivative of absorbance method improves algal detection limits, reduces the effect of background absorbance and the resolution of overlapping spectra. The presence of algae in water can cause a number of problems, and the method presented here can be used to effectively monitor algal concentration in various types of water samples and provide necessary information for decision making purposes.
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1. A device for detecting algae in water, comprising:
(i) a light source to generate light beams of electromagnetic radiation in the visible light spectrum;
(ii) a flow cell containing a water sample including windows to allow said light beams to transmit through said flow cell and water sample;
(iii) a spectrometer unit that receives said transmitted light beams penetrating said sample in said flow cell, and resolves said incident light beams into a specific visible absorbance spectrum pertaining to said sample;
(iv) a processor connected to said spectrometer unit programmed to:
a. compute the derivative of the visible absorbance spectrum through said flow cell;
b. compute from the derivative spectra the concentration of varying types of algae.
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The invention relates to the field of visible light spectrophotometry and more particularly it relates to a device for detecting algae concentration using first derivative of visible light absorbance.
The presence of algae in both surface and wastewater is one of the main causes of water quality deterioration (Al-Zboon and Al-Suhaili, 2009; Rodrigues et al., 2011). Algal growth in different parts of conventional wastewater treatment plants or aerated lagoon systems can result in false indications in the final effluent parameters, such as TSS, CBOD5 and COD (Heng et al., 2010; Chow et al., 1999; Gitzgerald, 1964). In surface water, the presence of algae creates nuisance surface scum, poor water clarity, and noxious odours (Abdel-Raouf et al., 2012; Aly and Sami, 2014). If this surface water is used to produce drinking water, the algae may lead to problems in the drinking water treatment process, such as reduced filter runs and an increase in the amount of disinfectant needed, which can increase the cost of the treatment (Horan, 1990).
In order to set up an efficient control and treatment process to minimize algal concentration in water samples, it is necessary to have access to a concentration measurement method which is quick, simple, and accurate, and which can detect low algal concentrations in different types of water. The methods currently used to determine algal concentration in different water samples include algal number, as prescribed in the Standard Methods for the Examination of Water and Wastewater (APHA, 1985), and the determination of chlorophyll extract concentration in relation to total algal concentration (Wasmund et al., 2006; Jones and Lee, 1982). Both of these methods are labour and time intensive, expensive, and require extensive laboratory preparation. Moreover, it is not clear how efficient the chlorophyll extraction process is or how its results are related to the real algal concentration in water solutions.
Recently, the use of real-time and inline spectrophotometric methods at water and wastewater treatment plants to measure different parameters, such as total organic carbon, disinfection by-product precursors, nitrates, and UV transmittance for UV disinfection have increased dramatically (James et al., 2003; Langergraber et al., 2004; Gibbons and Örmeci, 2013; Al Momani and Ormeci, 2014). These measurements are considered practical, quick, simple, and accurate for these industries.
Different studies have reported that the absorbance measurements of algae in water produce a spectrum with a maximum absorbance near the wavelength of red light (540-690 nm) (Gaigalas et al., 2009; UGWU et al., 2007; Liang et al., 2009; Sung et al., 2010). In some types of water and wastewater, the accuracy of the spectrophotometric measurements is affected by water turbidity and by the presence of other constituents in the water sample that mask the absorbance response or produce high levels of noise in the spectral background.
Spectral first and higher-order derivatives have been used by different studies to facilitate the location of the critical wavelength, to reduce low-frequency background noise, and to resolve overlapping spectra (Demetriades-Shah et al., 1990). However, it appears that no research work has explored the use of the first derivative of the absorbance spectra to determine the concentration of algae in an aqueous solution.
The foregoing examples of the related art and limitations related therewith are intended to be illustrative and not exclusive. Other limitations of the related art will become apparent to those of skill in the art upon a reading of the specification and a study of the figures.
The following embodiments and aspects thereof are described and illustrated in conjunction with systems, tools and methods which are meant to be exemplary and illustrative, not limiting in scope.
There is provided, in accordance with an embodiment, a system for detecting algae, comprising: an online spectrophotometer configured to measure an absorbance level of a sample from a monitored source, and a processor that is configured to apply an algorithm to the measured absorption level to determine the concentration of algae in the monitored source, wherein the detection algorithm is derived by calculating the first derivative of absorbance values for the monitored source and applying a calibration set of the first derivative of absorbance values obtained from a controlled source with known concentrations of algae.
In addition to the exemplary aspects and embodiments described above, further aspects and embodiments will become apparent by reference to the figures and by study of the following detailed description.
Thus the present disclosure provides a device for detecting algae in water, comprising:
The device is configured to detect the concentration of various algae species.
The device may be operated to measure the concentration of algae in distilled water, surface water, or wastewater.
The processor may be programmed to apply a smoothing technique to improve the signal to noise ratio in the absorbance data. An exemplary non-limiting smoothing technique is the Savitzky-Golay smoothing technique.
The device is constructed so that samples can be directly placed into the spectrometer unit for analysis with no additional sample preparation requirements.
The light source may be a tungsten lamp.
Alternatively, the light source may be an LED based light source.
The spectrometer unit may be a photodiode array based spectrometer.
Alternatively, the spectrometer unit is a monochromator.
The device may be configured to be immersed in a sample water such that the sample water is free to flow in and out of a substantially open flow cell area.
The flow cell is configured to allow sample water to flow through either continuously or in successive batches from a sample source to a sample drain.
A further understanding of the functional and advantageous aspects of the present disclosure can be realized by reference to the following detailed description and drawings.
Embodiments will now be described, by way of example only, with reference to the drawings, in which:
Various embodiments and aspects of the disclosure will be described with reference to details discussed below. The following description and drawings are illustrative of the disclosure and are not to be construed as limiting the disclosure. The Figures are not to scale. Numerous specific details are described to provide a thorough understanding of various embodiments of the present disclosure. However, in certain instances, well-known or conventional details are not described in order to provide a concise discussion of embodiments of the present disclosure.
As used herein, the terms, “comprises” and “comprising” are to be construed as being inclusive and open ended, and not exclusive. Specifically, when used in the specification and claims, the terms, “comprises” and “comprising” and variations thereof mean the specified features, steps or components are included. These terms are not to be interpreted to exclude the presence of other features, steps or components.
As used herein, the term “exemplary” means “serving as an example, instance, or illustration,” and should not be construed as preferred or advantageous over other configurations disclosed herein.
As used herein, the terms “about” and “approximately” are meant to cover variations that may exist in the upper and lower limits of the ranges of values, such as variations in properties, parameters, and dimensions. In one non-limiting example, the terms “about” and “approximately” mean plus or minus 10 percent or less.
Unless defined otherwise, all technical and scientific terms used herein are intended to have the same meaning as commonly understood to one of ordinary skill in the art.
An embodiment of the invention includes the apparatus described by
The foregoing description of the preferred embodiments of the invention has been presented to illustrate the principles of the invention and not to limit the invention to the particular embodiment illustrated. It is intended that the scope of the invention be defined by all of the embodiments encompassed within the following claims and their equivalents.
Ormeci, Banu, Glover, Andrew, Kollu, Kerim
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